PCO:0000001population of organismsPCO:0000008population growth rate2decreased1-phenyl 2-thiourea 2019-05-03T08:37:182019-05-03T08:37:18WikiUser_22all speciesWikiUser_6fishInhibition of tyrosinase tyrosinase Molecular2019-05-03T08:28:372019-05-03T08:28:37Reduction of L-DopaquinoneReduction of L-DopaquinoneCellular2019-05-03T08:29:402019-05-03T08:29:40Reduction in melanin levelReduction in melanin levelCellular2019-05-03T08:30:292019-05-03T08:30:29Reduction of melanosome levelReduction of melanosome levelTissue2019-05-03T08:31:072019-05-03T08:31:07Reduction fo Pigmentation pattern Reduction fo Pigmentation pattern Individual2019-05-03T08:31:562019-05-03T08:31:56Decrease, Population growth rateDecrease, Population growth ratePopulation<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">A population can be defined as a group of interbreeding organisms, all of the same species, occupying a specific space during a specific time (Vandermeer and Goldberg 2003, Gotelli 2008). As the population is the biological level of organization that is often the focus of ecological risk</span> <span style="color:black">assessments, population growth rate (and hence population size over time) is important to consider within the context of applied conservation practices.</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">If N is the size of the population and t is time, then the population growth rate (dN/dt) is proportional to the instantaneous rate of increase, r, which measures the per capita rate of population increase over a short time interval. Therefore, r, is a difference between the instantaneous birth rate (number of births per individual per unit of time; b) and the instantaneous death rate (number of deaths per individual per unit of time; d) [Equation 1]. Because r is an instantaneous rate, its units can be changed via division. For example, as there are 24 hours in a day, an r of 24 individuals/(individual x day) is equal to an r of 1 individual/(individual/hour) (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). </span></span></span></span></p>
<p style="margin-left:144px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Equation 1: r = b - d</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">This key event refers to scenarios where r < 0 (instantaneous death rate exceeds instantaneous birth rate).</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Examining r in the context of population growth rate:</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A population will decrease to extinction when the instantaneous death rate exceeds the instantaneous birth rate (r < 0). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black"> ● The smaller the value of r below 1, the faster the population will decrease to zero. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A population will increase when resources are available and the instantaneous birth rate exceeds the instantaneous death rate (r > 0)</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black"> ● The larger the value that r exceeds 1, the faster the population can increase over time </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A population will neither increase or decrease when the population growth rate equals 0 (either due to N = 0, or if the per capita birth and death rates are exactly balanced). For example, the per capita birth and death rates could become exactly balanced due to density dependence and/or to the effect of a stressor that reduces survival and/or reproduction (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Effects incurred on a population from a chemical or non-chemical stressor could have an impact directly upon birth rate (reproduction) and/or death rate (survival), thereby causing a decline in population growth rate. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● Example of direct effect on r: Exposure to 17b-trenbolone reduced reproduction (i.e., reduced b) in the fathead minnow over 21 days at water concentrations ranging from 0.0015 to about 41 mg/L (Ankley et al. 2001; Miller and Ankley 2004). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Alternatively, a stressor could indirectly impact survival and/or reproduction. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● Example of indirect effect on r: Exposure of non-sexually differentiated early life stage fathead minnow to the fungicide prochloraz has been shown to produce male-biased sex ratios based on gonad differentiation, and resulted in projected change in population growth rate (decrease in reproduction due to a decrease in females and thus recruitment) using a population model. (Holbech et al., 2012; Miller et al. 2022)</span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Density dependence can be an important consideration:</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● The effect of density dependence depends upon the quantity of resources present within a landscape. A change in available resources could increase or decrease the effect of density dependence and therefore cause a change in population growth rate via indirectly impacting survival and/or reproduction. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● This concept could be thought of in terms of community level interactions whereby one species is not impacted but a competitor species is impacted by a chemical stressor resulting in a greater availability of resources for the unimpacted species. In this scenario, the impacted species would experience a decline in population growth rate. The unimpacted species would experience an increase in population growth rate (due to a smaller density dependent effect upon population growth rate for that species). </span> </span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Closed versus open systems:</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● The above discussion relates to closed systems (there is no movement of individuals between population sites) and thus a declining population growth rate cannot be augmented by immigration. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● When individuals depart (emigrate out of a population) the loss will diminish population growth rate. </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Population growth rate applies to all organisms, both sexes, and all life stages.</span></span></span></span></p>
<p> </p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Population growth rate (instantaneous growth rate) can be measured by sampling a population over an interval of time (i.e. from time t = 0 to time t = 1). The interval of time should be selected to correspond to the life history of the species of interest (i.e. will be different for rapidly growing versus slow growing populations). The population growth rate, r, can be determined by taking the difference (subtracting) between the initial population size, N</span><sub><span style="font-size:9pt"><span style="color:black">t=0 </span></span></sub><span style="color:black">(population size at time t=0), and the population size at the end of the interval, N</span><sub><span style="font-size:9pt"><span style="color:black">t=1 </span></span></sub><span style="color:black">(population size at time t = 1), and then subsequently dividing by the initial population size. </span></span></span></span></p>
<p style="margin-left:96px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Equation 2: r = (N</span><sub><span style="font-size:9pt"><span style="color:black">t=1 </span></span></sub><span style="color:black">- N</span><sub><span style="font-size:9pt"><span style="color:black">t=0</span></span></sub><span style="color:black">) / N</span><sub><span style="font-size:9pt"><span style="color:black">t=0</span></span></sub></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">The diversity of forms, sizes, and life histories among species has led to the development of a vast number of field techniques for estimation of population size and thus population growth over time (Bookhout 1994, McComb et al. 2021). </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● For stationary species an observational strategy may involve dividing a habitat into units. After setting up the units, samples are performed throughout the habitat at a select number of units (determined using a statistical sampling design) over a time interval (at time t = 0 and again at time t = 1), and the total number of organisms within each unit are counted. The numbers recorded are assumed to be representative for the habitat overall, and can be used to estimate the population growth rate within the entire habitat over the time interval. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● For species that are mobile throughout a large range, a strategy such as using a mark-recapture method may be employed (i.e. tags, bands, transmitters) to determine a count over a time interval (at time = 0 and again at time =1). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Population growth rate can also be estimated using mathematical model constructs (for example, ranging from simple differential equations to complex age or stage structured matrix projection models and individual based modeling approaches), and may assume a linear or nonlinear population increase over time (Caswell 2001, Vandermeer and Goldberg 2003, Gotelli 2008, Murray and Sandercock 2020). The AOP framework can be used to support the translation of pathway-specific mechanistic data into responses relevant to population models and output from the population models, such as changing (declining) population growth rate, can be used to assess and manage risks of chemicals (Kramer et al. 2011). As such, this translational capability can increase the capacity and efficiency of safety assessments both for single chemicals and chemical mixtures (Kramer et al. 2011). </span></span></span></span></p>
<p style="text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">Some examples of modeling constructs used to investigate population growth rate:</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A modeling construct could be based upon laboratory toxicity tests to determine effect(s) that are then linked to the population model and used to estimate decline in population growth rate. Miller et al. (2007) used concentration–response data from short term reproductive assays with fathead minnow (<em>Pimephales promelas</em>) exposed to endocrine disrupting chemicals in combination with a population model to examine projected alterations in population growth rate. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A model construct could be based upon a combination of effects-based monitoring at field sites (informed by an AOP) and a population model. Miller et al. (2015) applied a population model informed by an AOP to project declines in population growth rate for white suckers (Catostomus commersoni) using observed changes in sex steroid synthesis in fish exposed to a complex pulp and paper mill effluent in Jackfish Bay, Ontario, Canada. Furthermore, a model construct could be comprised of a series of quantitative models using KERs that culminates in the estimation of change (decline) in population growth rate. </span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● A quantitative adverse outcome pathway (qAOP) has been defined as a mathematical construct that models the dose–response or response–response relationships of all KERs described in an AOP (Conolly et al. 2017, Perkins et al. 2019). Conolly et al. (2017) developed a qAOP using data generated with the aromatase inhibitor fadrozole as a stressor and then used it to predict potential population‐level impacts (including decline in population growth rate). The qAOP modeled aromatase inhibition (the molecular initiating event) leading to reproductive dysfunction in fathead minnow (Pimephales promelas) using 3 computational models: a hypothalamus–pituitary–gonadal axis model (based on ordinary differential equations) of aromatase inhibition leading to decreased vitellogenin production (Cheng et al. 2016), a stochastic model of oocyte growth dynamics relating vitellogenin levels to clutch size and spawning intervals (Watanabe et al. 2016), and a population model (Miller et al. 2007).</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● Dynamic energy budget (DEB) models offer a methodology that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources (Nisbet et al. 2000, Nisbet et al. 2011). Murphy et al. (2018) developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates.</span></span></span></span></p>
<p style="margin-left:48px; text-align:start"><span style="font-size:medium"><span style="font-family:Calibri,sans-serif"><span style="color:#000000"><span style="color:black">● Endogenous Lifecycle Models (ELMs), capture the endogenous lifecycle processes of growth, development, survival, and reproduction and integrate these to estimate and predict expected fitness (Etterson and Ankley, 2021). AOPs can be used to inform ELMs of effects of chemical stressors on the vital rates that determine fitness, and to decide what hierarchical models of endogenous systems should be included within an ELM (Etterson and Ankley, 2021).</span></span></span></span></p>
<p> </p>
<p>Consideration of population size and changes in population size over time is potentially relevant to all living organisms.</p>
Not SpecifiedUnspecificNot SpecifiedAll life stagesHigh<ul>
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2016-11-29T18:41:242023-01-03T09:09:06298bc292-91b9-47f7-9906-93f43cb87ac446827ce9-912f-4647-9b4d-24be7eb5da652019-05-03T08:33:132019-05-03T08:33:1346827ce9-912f-4647-9b4d-24be7eb5da65515c0737-0328-47f9-9bd7-68913a9e74442019-05-03T08:33:342019-05-03T08:33:34515c0737-0328-47f9-9bd7-68913a9e74447066d9d0-04e9-4ebc-99e6-43dadf65789d2019-05-03T08:35:002019-05-03T08:35:007066d9d0-04e9-4ebc-99e6-43dadf65789dc8531c3a-e842-46af-a14c-bc9f35e4454a2019-05-03T08:35:252019-05-03T08:35:25c8531c3a-e842-46af-a14c-bc9f35e4454a5d8d04ab-6382-4c74-896c-198b669be02c2019-05-03T08:36:202019-05-03T08:36:20Inhibition of tyrosinase leads to decreased population in fishtyrosinase, fish <p>Kichul Cho (kichul.cho@mabik.re.kr)</p>
<p>Environmental Safety Group, Korea Institute of Science and Technology (KIST) Europe, Campus E 7.1, 66123 Saarbruecken, Germany</p>
<p>Youngjun Kim (youngjunkim@kist-europe.de)</p>
<p>Environmental Safety Group, Korea Institute of Science and Technology (KIST) Europe, Campus E 7.1, 66123 Saarbruecken, Germany</p>
Open for citation & commentUnder DevelopmentIncluded in OECD Work Plan1.78<p>This AOP is designed to estimate changes in population trajectory of fishes resulting from the inhibition of the enzyme tyrosinase (TYR), which is rate-limiting in the control of melanogenesis. Since tyrosinase inhibition leads to the decrease of DOPAquinone synthesis, tyrosinase inhibition by unknown or known chemicals will lead to L DOPA quinone inhibition and decrease of eu - and pheo -melanogenesis. Subsequently, these KEs possibly lead to the decline of teleost population. Hence this AOP could support the use of an in vitro high throughput screening assay for tyrosinase inhibition to identify chemicals that may reduce pigmentation in fish leaving them vulnerable to predation and unable to perform important social behaviors important to their survival and reproduction. Decreased population trajectory resulting from reduced pigmentation patterns in the fish body is a potential endpoint for eco-toxicity. The proposed endpoint will provide useful high throughput risk assessment screening tools for potential chemicals. Consequently, this AOP can be applied to the prediction of eco-toxicity caused by the inhibition of TYR. </p>
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<p>The present AOP shows a tyrosinase (TYR) inhibition-mediated adverse outcome (AO) in fishes. TYR is the rate-limiting enzyme controlling the induction of melanogenesis in diverse colored patterns in aquatic organisms. The significant reactions of TYR can be considered that the tyrosinase inhibitor-induced depigmentation reduces the trajectory of fishes. </p>
<p><strong>Acknowledgements</strong>: This research was supported by the National Research Council of Science & Technology(NST) grant by the Korea government (MSIP) (No. CAP-17-01-KIST Europe)</p>
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<p>Maintenance of sustainable fish and wildlife populations (i.e., adequate to ensure long-term delivery of valued ecosystem services) is a widely accepted regulatory goal upon which risk assessments and risk management decisions are based.</p>
adjacentHighHighadjacentHighHighadjacentHighHighadjacentHighHighadjacentLowModerate<p>Inhibition of TYR (KER 1627) can be caused by chemical inhibitors such as 1-phenyl 2-thiourea (PTU), sesamol, arbutin, Kojic acid, bis(4-hydroxybenzyl) and etc. (J. Karlsson et al., 2001; W. C. Chen et al., 2015; Baek and Lee, 2015; S. H. Cha et al., 2011). </p>
<p>TYR inhibition as Key event 1891, the MIE for the present AOP, results in reduction of L-Dopaquinone level in the melanocyte via inhibition of L-DOPA oxidation moreover, it results in attenuation of eumelanin and pheomelanin biosynthesis (T. S. Chang, 2012; J. Choi and J. G. Jee, 2015; S. Y. Lee, 2016; A. J. Winder and H. Harris, 1991; W. C. Chen et al., 2015).</p>
<p>There are perhaps a non-adjacent relationship linking event 1629 to event 1631 that the lowered level of melanin biosynthesis by TYR inhibition simultaneously leads to depigmentation in skin tissue and diminished pigmentation pattern in the fish body (L. E. Jao et al., 2013; S. Y. Wu et al., 2015; S. H. Baek and S. H. Lee, 2015; W. C. Chen et al., 2015; D. C. Kim et al., 2017).</p>
ModerateMixedNot SpecifiedNot Otherwise SpecifiedHigh<table border="1" cellpadding="0" cellspacing="0" style="width:841px">
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<p><strong><u>To do</u></strong></p>
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<p>Building the AOP frame</p>
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<p>Development of KEs</p>
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<p>Production of experimental data</p>
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<p>Overall assessment of the AOP</p>
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<p>Biological domain of applicability</p>
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<p>Essentiality of all KEs</p>
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<p>Evidence supporting all KERs</p>
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<p>Quantitative WoE considerations</p>
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<p>Quantitative understanding for each KER</p>
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<p>Inhibition of TYR (KER 1627) can be caused by chemical inhibitors such as 1-phenyl 2-thiourea (PTU), sesamol, arbutin, Kojic acid, bis(4-hydroxybenzyl) and etc. (J. Karlsson et al., 2001; W. C. Chen et al., 2015; Baek and Lee, 2015; S. H. Cha et al., 2011). </p>
<p>TYR inhibition as Key event 1891, the MIE for the present AOP, results in reduction of L-Dopaquinone level in the melanocyte via inhibition of L-DOPA oxidation moreover, it results in attenuation of eumelanin and pheomelanin biosynthesis (T. S. Chang, 2012; J. Choi and J. G. Jee, 2015; S. Y. Lee, 2016; A. J. Winder and H. Harris, 1991; W. C. Chen et al., 2015).</p>
<p>There are perhaps a non-adjacent relationship linking event 1629 to event 1631 that the lowered level of melanin biosynthesis by TYR inhibition simultaneously leads to depigmentation in skin tissue and diminished pigmentation pattern in the fish body (L. E. Jao et al., 2013; S. Y. Wu et al., 2015; S. H. Baek and S. H. Lee, 2015; W. C. Chen et al., 2015; D. C. Kim et al., 2017).</p>
<p>First, TYR can convert L-tyrosine directly to L-3,4-dihydroxyphenylalanine (L-DOPA) which is a precursor of (2<em>S</em>)-2-Amino-3-(3,4-dioxocyclohexa-1,5-dien-1-yl)propanoic acid (L-Dopaquinone) synthesis; Second, TYR catalyzes the oxidation of L-DOPA to the L-Dopaquinone which is the reactive intermediate for the eumelanin and pheomelanin synthesis. Pigment patterns in common fishes usually play a significant role to communicate within species, intersexual interactions, escape potential in the eyes of predators and finding shoal mate (Price et al., 2008; C. L. Peichel et al., 2004; R. E. Engeszer et al., 2004)</p>
<p>It will be come soon,</p>
<p>In fish as behavioral ecology, color patterns are often multi-component signals, composed of pigment-based and physiological regulation that can be used to communicate in both inter- and intrasexual interactions in population. This endpoint is essential and useful for screening of pigmentation effects on the photosensitive context for skin toxicity screening and relevant to teratogenic effects.</p>
High<p><strong>References</strong></p>
<p> </p>
<p>Karlsson, J., et al. (2001). Generating transparent zebrafish: a refined method to improve detection of gene expression during embryonic development. Marine Biotechnology, 3(6), 522-527.</p>
<p>Chen, W. C., et al. (2015). Discovery of highly potent tyrosinase inhibitor, T1, with significant anti-melanogenesis ability by zebrafish in vivo assay and computational molecular modeling. Scientific reports, 5, 7995.</p>
<p>Baek, S. H., & Lee, S. H. (2015). Sesamol decreases melanin biosynthesis in melanocyte cells and zebrafish: Possible involvement of MITF via the intracellular cAMP and p38/JNK signalling pathways. Experimental dermatology, 24(10), 761-766.</p>
<p>Cha, S. H., et al. (2011). Screening of marine algae for potential tyrosinase inhibitor: those inhibitors reduced tyrosinase activity and melanin synthesis in zebrafish. The Journal of dermatology, 38(4), 354-363.</p>
<p>Chang, T. S. (2012). Natural melanogenesis inhibitors acting through the down-regulation of tyrosinase activity. Materials, 5(9), 1661-1685.</p>
<p>Choi, J., & Jee, J. G. (2015). Repositioning of thiourea-containing drugs as tyrosinase inhibitors. International journal of molecular sciences, 16(12), 28534-28548.</p>
<p>Lee, S. Y., Baek, N., & Nam, T. G. (2016). Natural, semisynthetic and synthetic tyrosinase inhibitors. Journal of enzyme inhibition and medicinal chemistry, 31(1), 1-13.</p>
<p>Winder, A. J., & Harris, H. (1991). New assays for the tyrosine hydroxylase and dopa oxidase activities of tyrosinase. European journal of biochemistry, 198(2), 317-326.</p>
<p>Chen, W. C., et al. (2015). Discovery highly potent tyrosinase inhibitor, T1, with significant anti-melanogenesis ability by zebrafish in vivo assay and computational molecular modeling. Scientific reports, 5, 7995.</p>
<p>Jao, L. E., et al. (2013). Efficient multiplex biallelic zebrafish genome editing using a CRISPR nuclease system. Proceedings of the National Academy of Sciences, 110(34), 13904-13909.</p>
<p>Wu, S. Y., et al. (2015). 4-(Phenylsulfanyl) butan-2-one suppresses melanin synthesis and melanosome maturation in vitro and in vivo. International journal of molecular sciences, 16(9), 20240-20257.</p>
<p>Baek, S. H., & Lee, S. H. (2015). Sesamol decreases melanin biosynthesis in melanocyte cells and zebrafish: Possible involvement of MITF via the intracellular cAMP and p38/JNK signalling pathways. Experimental dermatology, 24(10), 761-766.</p>
<p>Chen, W. C., et al. (2015). Discovery of highly potent tyrosinase inhibitor, T1, with significant anti-melanogenesis ability by zebrafish in vivo assay and computational molecular modeling. Scientific reports, 5, 7995.</p>
<p>Kim, D. C., et al. (2017). p-coumaric acid potently down-regulates zebrafish embryo pigmentation: Comparison of in vivo assay and computational molecular modeling with phenylthiourea. Biomedical Science Letters, 23(1), 8-16.</p>
<p>Price, A. C., et al. (2008). Pigments, patterns, and fish behavior. Zebrafish, 5(4), 297-307.</p>
<p>Peichel, C. L. (2004). Social behavior: how do fish find their shoal mate?. Current Biology, 14(13), R503-R504.</p>
<p>Engeszer, R. E., et al. (2004). Learned social preference in zebrafish. Current Biology, 14(10), 881-884.</p>
<p>Slavík, O., et al. (2016). How does agonistic behaviour differ in albino and pigmented fish?. PeerJ, 4, e1937.</p>
<p>Ren, J. Q., et al. (2002). Behavioral visual responses of wild-type and hypopigmented zebrafish. Vision research, 42(3), 293-299.</p>
<p>Slavík, O., et al. (2015). Ostracism of an albino individual by a group of pigmented catfish. Plos one, 10(5), e0128279.</p>
<p>Onyia, U. L., et al. (2016). Growth and survival of normal coloured and albino clarias gariepinus and their reciprocal hybrids. Nigerian Journal of Fisheries and Aquaculture, 4(1), 22-27.</p>
<p>Bondari, K. (1984). Comparative performance of albino and normally pigmented channel catfish in tanks, cages, and ponds. Aquaculture, 37(4), 293-301.</p>
<p>Pérez-Carpinell, J. O. A. Q. U. I. N., et al. (1992). Vision defects in albinism. Optometry and vision science: official publication of the American Academy of Optometry, 69(8), 623-628.</p>
<p>Cho, K., Ryu, C. S., Jeong, S., & Kim, Y. (2020). Potential adverse effect of tyrosinase inhibitors on teleosts: A review. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology, 228, 108655.</p>
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